explain_lineage

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only traversal but never states the operation is non-mutating, nor what happens for an unknown or non-existent metric, nor any permission requirements. Behavior beyond the conceptual output shape is largely undisclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, both earning their place: the first defines the resource and its boundary, the second states the use case. Purpose is front-loaded with zero filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with an output schema (so return values need no prose) and full schema coverage, the description covers purpose and trigger adequately. Only the silence on failure/edge behavior with no annotations keeps it from being fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single `metric` parameter, which already documents it as the canonical metric name. The description adds no naming convention, format, or lookup guidance beyond that, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific resource and scope: the chain of dbt models producing a metric, from source to mart. This is clearly distinct from query_metric (returns numbers) and describe_metric (definition), though it never names those siblings explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use para responder de onde vem o número" gives a clear, concrete usage context — answering provenance questions about a metric. No exclusions or named alternatives are offered, but the trigger condition is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.